Named Entities as New Features for Czech Document Classification

Abstract

Abstract. This paper is focused on automatic document classification. The results will be used to develop a real application for the Czech News Agency. The main goal of this work is to propose new features based on the Named Entities (NEs) for this task. Five different approaches to employ NEs are suggested and evaluated on a Czech newspaper corpus. We show that these features do not improve significantly the score over the baseline word-based features. The classification error rate improvement is only about 0.42% when the best approach is used.

SAPKOS: Experimental Czech Multi-label Document Classification and Analysis System

“…In [9], three different multi-label classification approaches are compared and evaluated. Other recent works propose novel features based on named entities [14] or on unsupervised machine learning [3].…”